Image processing has a significant impact in medical filed, such as Digital Subtraction Angiography (DSA), Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), Computed tomography (CT), Computed Tomography Angiography (CTA), Ultrasound Scanning (US), Positron Emission Tomography (PET), Single-Photon Emission Computerized Tomography (SPECT), CT-MR, CT-PET, CE-SPECT, DSA-MR, PET-MR, PET-US, SPECT-US, TMS (transcranial magnetic stimulation)-MR, US-CT, US-MR, X-ray-CT, X-ray-MR, X-ray-portal, X-ray-US, Video-CT, Vide-US, or the like, or any combination thereof. An image segmentation (or “recognition,” “classification,” “extraction,” “identification,” etc.) may be performed to establish a realistic subject model by dividing or partitioning a medical image into one or more sub-regions. Segmentation is a procedure of image processing and a means to extract quantitative information relating to a target subject from a medical image. Different subjects may be segmented in different ways to improve the accuracy of the segmentation. The accuracy of an image segmentation may affect the accuracy of a disease diagnosis. Thus, it is desirable to improve the accuracy of image segmentation.